Hi 👋! I am Giovanni and I am a Research Scientist at Fondazione Bruno Kessler (FBK).
My research focuses on the algorithmic challenges involved in ensuring human oversight of AI systems and understanding their effects when deployed in social contexts.
I hold a PhD from the University of Trento (cum laude), advised by Bruno Lepri and Andrea Passerini.
I was also part of the European Laboratory for Learning and Intelligent Systems (ELLIS) PhD network, through which I spent some time at the Max Planck Institute for Software Systems working with Manuel Gomez Rodriguez.
Throughout my academic journey, I conducted research as a visiting scientist or intern at several institutions, including the European Commission, Google X, and CERN.
Before my PhD, I was a Research Scientist at VUI, Inc., a Boston-based startup (now acquired) developing innovative conversational AI technologies.
In the past, I have also contributed to several open-source scientific libraries (e.g., Shogun).
Latest News
- 12/2025: I'll be serving as PC Web Chair for FAccT 2026 (ACM Conference on Fairness, Accountability, and Transparency)! We are now accepting submissions on OpenReview!
- 11/2025: "Revisiting (Un)Fairness in Recourse by Minimizing Worst-Case Social Burden" (with A. Barrainkua, J. A. Lozano, and N. Quadrianto) was accepted at AAAI 2026 as an oral!
- 11/2025: We have released a new preprint "Multiclass Local Calibration With the Jensen-Shannon Distance" (with C. Barbera, L. Perini, A. Passerini and A. Pugnana).
- 10/2025: We have released a new preprint "To Ask or Not to Ask: Learning to Require Human Feedback" (with A. Pugnana, C. Barbera, R. Pellungrini, B. Lepri and A. Passerini).
- 09/2025: Our latest paper (with E. Purificato, E. Gomez, B. Lepri, A. Passerini and C. Consonni) received the Best Full Paper Award 🏆 at ACM RecSys 2025!
- 09/2025: We have released a new preprint "Who Pays for Fairness? Rethinking Recourse under Social Burden" (with A. Barrainkua, J. A. Lozano, and N. Quadrianto).
- 07/2025: "You Don't Bring Me Flowers: Mitigating Unwanted Recommendations Through Conformal Risk Control" (with E. Purificato, E. Gomez, B. Lepri, A. Passerini and C. Consonni) was accepted at ACM RecSys 2025!
- 05/2025: I joined Fondazione Bruno Kessler (FBK) as a Research Scientist!
- 04/2025: "Time Can Invalidate Algorithmic Recourse" (with S. Teso, B. Lepri, and A. Passerini) has been accepted to FAccT 2025! See you in Athens!
- Older News
Publications & Preprints
- Multiclass Local Calibration With the Jensen-Shannon Distance
Cesare Barbera, Lorenzo Perini, Giovanni De Toni,, Andrea Passerini, Andrea Pugnana
Preprint
[paper][code]
- To Ask or Not to Ask: Learning to Require Human Feedback
Andrea Pugnana*, Giovanni De Toni*, Cesare Barbera*, Roberto Pellungrini, Bruno Lepri, Andrea Passerini
Preprint (* equal contribution)
[paper][code]
- Revisiting (Un)Fairness in Recourse by Minimizing Worst-Case Social Burden
Ainhize Barrainkua, Giovanni De Toni, Jose Antonio Lozano, Novi Quadrianto
to appear in AAAI 2026
Oral
[paper][code]
- 🏆 You Don’t Bring Me Flowers: Mitigating Unwanted Recommendations Through Conformal Risk Control
Giovanni De Toni, Erasmo Purificato, Emilia Gomez, Andrea Passerini, Bruno Lepri, Cristian Consonni
RecSys: 19th ACM Conference on Recommender Systems (2025)
Best Full Paper Award at 19th ACM Conference on Recommender Systems (ACM RecSys 2025)
[paper][code]
- Time Can Invalidate Algorithmic Recourse
Giovanni De Toni, Stefano Testo, Bruno Lepri, Andrea Passerini
FAccT: ACM Conference on Fairness, Accountability, and Transparency (2025)
[paper][code]
- Towards Human-AI Complementarity with Predictions Sets
Giovanni De Toni, Nastaran Okati, Suhas Thejaswi, Eleni Straitouri, Manuel Gomez-Rodriguez
NeurIPS (2024)
[paper][code]
- 🏆 Preference Elicitation in Interactive and User-centered Algorithmic Recourse: an Initial Exploration
Seyedehdelaram Esfahani, Giovanni De Toni, Bruno Lepri, Andrea Passerini, Katya Tentori, Massimo Zancanaro
ACM UMAP (2024)
Best Short Paper Runner-up at the 32nd ACM UMAP Conference (2024)
[paper][code]
- Personalized Algorithmic Recourse with Preference Elicitation
Giovanni De Toni, Paolo Viappiani, Stefano Teso, Bruno Lepri, Andrea Passerini
Transactions on Machine Learning Research (2024)
[paper][code]
- Synthesizing explainable counterfactual policies for algorithmic recourse with program synthesis
Giovanni De Toni, Bruno Lepri, Andrea Passerini
Machine Learning (2023)
[paper][code]